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Texture features in the Shearlet domain for histopathological image classification

Overview of attention for article published in BMC Medical Informatics and Decision Making, December 2020
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Mentioned by

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1 X user

Citations

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17 Dimensions

Readers on

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11 Mendeley
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Title
Texture features in the Shearlet domain for histopathological image classification
Published in
BMC Medical Informatics and Decision Making, December 2020
DOI 10.1186/s12911-020-01327-3
Pubmed ID
Authors

Sadiq Alinsaif, Jochen Lang

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 11 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 11 100%

Demographic breakdown

Readers by professional status Count As %
Other 2 18%
Librarian 1 9%
Researcher 1 9%
Student > Doctoral Student 1 9%
Student > Bachelor 1 9%
Other 3 27%
Unknown 2 18%
Readers by discipline Count As %
Computer Science 3 27%
Engineering 2 18%
Medicine and Dentistry 2 18%
Biochemistry, Genetics and Molecular Biology 1 9%
Unknown 3 27%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 16 December 2020.
All research outputs
#20,675,093
of 23,269,984 outputs
Outputs from BMC Medical Informatics and Decision Making
#1,831
of 2,022 outputs
Outputs of similar age
#431,222
of 506,176 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#43
of 52 outputs
Altmetric has tracked 23,269,984 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,022 research outputs from this source. They receive a mean Attention Score of 4.9. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 506,176 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 52 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.